| 基于改进阈值的VGG网络的新冠肺炎CT图像自动诊断算法 |
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| 引用本文： | 翁羽洁,李忠贤,姬宇程,薄素玲,梁莹.基于改进阈值的VGG网络的新冠肺炎CT图像自动诊断算法[J].中国医学物理学杂志,2022,0(6):731-736. |
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| 作者姓名： | 翁羽洁 李忠贤 姬宇程 薄素玲 梁莹 |
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| 作者单位： | 内蒙古医科大学计算机信息学院， 内蒙古 呼和浩特 010110 |
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| 摘 要： | 肺部CT能够较准确地鉴定新冠肺炎病例，但医生工作量较大，本研究提出一种基于改进阈值的VGG网络的新冠肺炎CT图像自动诊断算法，通过该模型可快速准确地完成新冠肺炎病例的自动识别，为进一步控制其传播提供帮助。通过比较卷积神经网络VGG中的VGG-11、VGG-13、VGG-16，获得准确率较高的新冠肺炎CT图像自动诊断模型VGG-13，并在此基础上通过改进阈值的方式使准确率由86%提高到了89%，进一步提高诊断的准确性。
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| 关 键 词： | 新冠肺炎 VGG CT图像 卷积神经网络 自动诊断 |
Automatic diagnosis algorithm for COVID-19 CT images using improved threshold-based VGG network |
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| WENG Yujie,LI Zhongxian,JI Yucheng,BO Suling,LIANG Ying.Automatic diagnosis algorithm for COVID-19 CT images using improved threshold-based VGG network[J].Chinese Journal of Medical Physics,2022,0(6):731-736. |
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| Authors: | WENG Yujie LI Zhongxian JI Yucheng BO Suling LIANG Ying |
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| Institution: | College of Computer and Information, Inner Mongolia Medical University, Hohhot 010110, China |
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| Abstract: | Lung CT can accurately identify COVID-19, but the workload of doctors is relatively large. An automatic diagnosis algorithm for COVID-19 CT image using improved threshold-based VGG network is proposed. The model can quickly and accurately complete the automatic identification of COVID-19 cases, and provide help for further control of its spread. By comparing VGG-11, VGG-13 and VGG-16 in convolutional neural network VGG, the automatic diagnosis model for COVID-19 CT image with high accuracy is obtained. On this basis, the accuracy is enhanced from 86% to 89% by modifying the threshold, further improving the accuracy of diagnosis. |
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| Keywords: | COVID-19 VGG CT image convolutional neural network automatic diagnosis |
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